Hierarchical Node Discovery in Distributed Computing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Distributed computing systems face challenges in managing the allocation and deployment of computing resources within enterprise environments, particularly due to competing and variable computing requirements across different business groups, making it difficult to efficiently organize and administer these systems.
Innovation Solution
A multi-level, hierarchical organizational model is implemented, with control nodes that automatically detect and manage computing nodes, allocate resources, and deploy them based on attributes, using a fabric, domain, tier, and node structure to efficiently manage computing functions and resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual management methods are used for distributed computing systems, then system organization and administration can be performed, but the efficiency and flexibility of resource allocation deteriorate due to competing business group requirements
Solution Approach 1:
The system implements automated self-service through the organizational model that enables computing nodes to be automatically discovered, inventoried, and allocated based on predefined policies. The control node autonomously manages resource distribution without manual intervention, allowing the system to self-regulate according to business group requirements and dynamically adjust allocations based on changing demands.
Solution Approach 2:
The patent segments the distributed computing system into a hierarchical organizational model with multiple levels (enterprise level, business group level, and computing node level). This segmentation allows independent management of different business groups with competing requirements while maintaining overall system coordination through the control node, thereby reducing management complexity while improving allocation efficiency.
2Extent of automation
If automated node detection and deployment is implemented, then resource allocation efficiency improves, but the extent of automation increases system complexity
Solution Approach 1:
The system performs preliminary actions by pre-defining the organizational model structure, node requirements, and allocation policies before actual resource deployment. The control node is pre-configured with the hierarchical model framework, enabling it to automatically discover and inventory nodes as they join the network without requiring complex real-time decision-making logic, thus managing automation complexity effectively.
3Adaptability or versatility
If hierarchical organizational model is implemented, then adaptability to varying computing requirements improves, but the device complexity increases due to multiple management levels
Solution Approach 1:
The patent introduces a hierarchical dimensional structure with multiple levels (enterprise, business group, and node levels) to manage complexity. By organizing resources vertically across these dimensions rather than horizontally, the system achieves high adaptability to varying business group requirements while maintaining manageable complexity at each level through the control node's coordinated management.
Data Source
AI summary
A distributed computing system conforms to a multi-level, hierarchical organizational model. One or more control nodes provide for the efficient and automated allocation and management of computing functions and resources within the distributed computing system in accordance with the organization model. The model includes four distinct levels: fabric, domains, tiers and nodes that provide for the logical abstraction and containment of the physical components as well as system and service application software of the enterprise. A user, such as a system administrator, interacts with the control nodes to logically define the hierarchical organization of distributed computing system. The control node detects the addition of a node added to the network and automatically identifies attributes for the detected node.